Various abbreviations that appear in the specification and/or in the drawing figures are defined as follows:
3GPP 3rd generation partnership project
ASIC application specific integrated circuit
BER bit error rate
DFT discrete Fourier transform
GMD geometric means decomposition
IMT international mobile telecommunications
MIMO multiple input multiple output
OFDM orthogonal frequency division multiplexing
QLD QL decomposition
QRD QR decomposition
SVD singular value decomposition
VQ vector quantization
WIMAX worldwide interoperability for microwave access (IEEE 802.16)
WLAN wireless local area network
The SVD-based beamforming (SVD-BF) has been known to provide a good beamforming performance to achieve an adequate capacity. Optimal beamforming requires channel state information in the form of the beamforming matrix for each MIMO-OFDM subcarrier (see, for example, G. G. Raleigh and J. M. Cioffi, “SPATIO-TEMPORAL CODING FOR WIRELESS COMMUNICATION,” IEEE Trans. on Commun., vol. 46, pp. 357-366, March 1998; and H. Bölcskei and A. J. Paulraj, “ON THE CAPACITY OF OFDM-BASED SPATIAL MULTIPLEXING SYSTEMs,” IEEE Trans. on Commun., vol. 50, pp. 225-234, February 2002). However, application of SVD-BF is limited for use to a narrow bandwidth MIMO system. In a MIMO-OFDM system SVD-BF is implemented on a per subcarrier basis and, as a result, as the DFT size increases the computational burden to find beamforming matrix and feedback requirements per subcarrier also increases (see, for example, J. Choi and R. W. Heath, “INTERPOLATION BASED TRANSMIT BEAMFORMING FOR MIMO-OFDM WITH LIMITED FEEDBACK,” IEEE Trans. on Signal Processing, vol. 53, pp. 4125-4135, December 2005). Also, SVD-BF is generally difficult to implement in a limited feedback closed-loop environment.
One previously proposed solution is to use a quantized feedback to convey the channel information to the transmitter. In Choi et al. a limited feedback architecture that combines beamforming vector quantization and smart vector interpolation is proposed. In this system, the receiver feeds back a fraction of the information about the optimal beamforming matrices to the transmitter and the transmitter computes the beamforming matrices for all subcarriers through interpolation.
In a VQ-based beamforming method a generalized Lloyd algorithm (J. C. Roh and B. D. Rao, “TRANSMIT BEAMFORMING IN MULTIPLE-ANTENNA SYSTEMS WITH FINITE RATE FEEDBACK: A VQ-BASED APPROACH,” IEEE Trans. on Inform. Theory, vol. 52, pp. 110′-1112, 2006) or a Grassmannian method has been used to design the beamformer (D. J. Love, R. W. H. Jr., and T. Strohmer, “GRASSMANNIAN BEAMFORMING FOR MULTIPLE-INPUT MULTIPLE-OUTPUT WIRELESS SYSTEMS,” IEEE Trans. on Inform. Theory, vol. 49, pp. 2735-2747, 2003).
The sharing of codebooks in the transmitter and the receiver can be used to reduce the feedback information. This basic approach has been proposed for use over frequency-selective channels (see B. Mondal and R. W. H. Jr., “ALGORITHMS FOR QUANTIZED PRECODING IN MIMO OFDM BEAMFORMING SYSTEMS,” Proc. SPIE Int. Soc. Opt. Eng., vol. 5847, pp. 80-87, 2005), which clusters a group of subcarriers and chooses a common frequency-domain representation of the channel information for each group. In S. Zhou, B. Li, and P. Willetty, “RECURSIVE AND TRELLIS-BASED FEEDBACK REDUCTION FOR MIMO-OFDM WITH RATE-LIMITED FEEDBACK,” IEEE Trans. on Wireless Communications, vol. 5, pp. 3400-3405, December 2006, each beamforming vector is drawn from a codebook with finite size. The receiver determines the optimal beamforming vector on each subcarrier depending on the channel realization, and informs the transmitter. Using the fact that the channel responses across OFDM subcarriers are highly correlated, the amount of information to be fed back can be reduced by selecting the optimal beamforming vectors sequentially across the subcarriers.
To reduce the amount of feedback information and the computational complexity, a quasi-SVD-BF method was proposed to use only one feedback of the beamforming matrix (see K. J. Kim, M. O. Pun, and R. A. Iltis, “QRD-BASED PRECODED MIMO-OFDM SYSTEMS WITH REDUCED FEEDBACK”, ICC2008, pp. 708-712, May 2008).